多特征相结合的带噪语音端点检测算法的研究

Study on endpoint detection based on multi-characteristic jointed in noisy environment

提出了一种抗噪声的端点检测新方法。针对谱熵特征对清音的检测性能以及抗噪声性能较差的缺点,结合对清音检测性能较好的短时过零率特征,以及抗噪声性能良好的美尔倒谱距离特征,实现了基于多种特征相结合的抗噪声的语音端点检测。仿真实验表明,该方法能显著提高端点检测在高噪声环境下的检测性能。

This paper proposes a new method of speech endpoint detection in high noisy environment.In order to solve the problem of the less effective detection of surd and the poor anti-noise performance in spectrum entropy characteristic,this paper combines short-time ZCR characteristic which has a better detection of surd with Mel cepstral distance characteristic which has a good anti-noise performance to realize the endpoint detection based on multi-characteristics in high noise environment.The simulation shows that the new method can significantly improve the detection performance in high noise environment.